Introduction to Semantic Web and Ontologies Hasan TÜRKSOY Compiled, partly based on various online tutorials and presentations, with respect to their authors

Introduction to Semantic Web Based on tutorials and presentations: D. Lee, F. Harmelen, M. Arumugam, C. Goble, I. Horrocks, N. F. Noy, D.L. McGuinness, J. Broekstra, M. Klein, S. Decker, D. Fensel, DERI Group, H. Knublauch, N. Drummond, M. Horridge

History of the Semantic Web Web was “invented” by Tim Berners-Lee (amongst others), a physicist working at CERN TBL’s original vision of the Web was much more ambitious than the reality of the existing (syntactic) Web: TBL (and others) have since been working towards realising this vision, which has become known as the Semantic Web – E.g., article in May 2001 issue of Scientific American… “... a goal of the Web was that, if the interaction between person and hypertext could be so intuitive that the machine-readable information space gave an accurate representation of the state of people's thoughts, interactions, and work patterns, then machine analysis could become a very powerful management tool, seeing patterns in our work and facilitating our working together through the typical problems which beset the management of large organizations.”

Where we are Today: the Syntactic Web [Hendler & Miller 02]

The Syntactic Web is… A place where computers do the presentation (easy) and people do the linking and interpreting (hard). – A hypermedia, a digital library A library of documents called (web pages) interconnected by a hypermedia of links – A database, an application platform A common portal to applications accessible through web pages, and presenting their results as web pages – A platform for multimedia BBC Radio 4 anywhere in the world! Terminator 3 trailers! – A naming scheme Unique identity for those documents Why not get computers to do more of the hard work? [Goble 03]

Hard Work using the Syntactic Web… Complex queries involving background knowledge –Find information about “animals that use sonar but are not either bats, dolphins or whales” Locating information in data repositories –Travel enquiries –Prices of goods and services –Results of human genome experiments Delegating complex tasks to web “agents” –Book me a holiday next weekend somewhere warm, not too far away, and where they speak French or English Almost impossible for machines and too hard for people without automation, e.g., Barn Owl

What is the Problem? Consider a typical web page: Markup consists of: –rendering information (e.g., font size and colour) –Hyper-links to related content Semantic content is accessible to humans but not (easily) to computers…

What information can we see… WWW2002 The eleventh international world wide web conference Sheraton waikiki hotel Honolulu, hawaii, USA 7-11 may location 5 days learn interact Registered participants coming from australia, canada, chile denmark, france, germany, ghana, hong kong, india, ireland, italy, japan, malta, new zealand, the netherlands, norway, singapore, switzerland, the united kingdom, the united states, vietnam, zaire Register now On the 7 th May Honolulu will provide the backdrop of the eleventh international world wide web conference. This prestigious event … Speakers confirmed Tim berners-lee Tim is the well known inventor of the Web, … Ian Foster Ian is the pioneer of the Grid, the next generation internet …

What information can a machine see…                          

Solution: XML markup with “meaningful” tags?                       …

But What About…                       …

Still the Machine only sees…                        

Need to Add “Semantics” External agreement on meaning of annotations – E.g., Dublin Core Agree on the meaning of a set of annotation tags – Problems with this approach Inflexible Limited number of things can be expressed Use Ontologies to specify meaning of annotations – Ontologies provide a vocabulary of terms – New terms can be formed by combining existing ones – Meaning (semantics) of such terms is formally specified – Can also specify relationships between terms in multiple ontologies

14 Dublin Core A set of fifteen basic properties for describing generalised Web resources ISO Standard (February 2003): The Dublin Core Metadata Initiative is an open forum engaged in the development of interoperable online metadata standards that support a broad range of purposes and business models.

15 Dublin Core (15 basic properties): Title Creator Subject Description Publisher Contributor Date Type Format Identifier Source Language Relation Coverage Rights

Dublin Core Example

Semantic Web basics...  RDF: stands for Resource Description Framework is a W3C standard, which provides tool to describe Web resources provides interoperability between applications that exchange machine-understandable information  RDF Schema: – is a W3C standard which defines vocabulary for RDF – organizes this vocabulary in a typed hierarchy (Class, Property, type, subClassOf, subPropertyOf, range, domain) – capable to explicitly declare semantic relations between vocabulary terms

Mary Director Secretary to_be_in_ love_with has_job John has_homepage Ontology RDF – Semantic Web over Web Resources

The RDF Data Model Statements are triples: Can be represented using XML serialisation, e.g.: Statements describe properties of resources All things (including properties) being described by RDF expressions are called resources A resource is a URI representing a (class of) object(s): –a document, a picture, a paragraph on the Web; – –a book in the library, a real person (?) –isbn:// –…–…

URI Venn diagram of Uniform Resource Identifier (URI) scheme categories. Schemes in the URL (locator) and URN (name) categories both function as resource IDs, so URL and URN are subsets of URI. They are also, generally, disjoint sets. However, many schemes can't be categorized as strictly one or the other, because all URIs can be treated as names, and some schemes embody aspects of both categories – or neither. –

Example of RDF Statement Subject (resource) Predicate (property)Creator Object (literal)“Ora Lassila” Ora Lassila is the creator of the resource

RDF Example (serialization syntax) Ora Lassila is the creator of the resource <rdf:Description about= " Ora Lassila 's' is a specific namespace prefix, e.g. xmlns:s="

What is RDFS ? RDF Schema – Defines vocabulary for RDF – Organizes this vocabulary in a typed hierarchy ( Class, subClassOf, type, Property, subPropertyOf ) Rich, web-based publication format for declaring semantics (XML for exchange) Capability to explicitly declare semantic relations between vocabulary terms

RDF Schema Semantic network on the Web Nodes are identified by URIs rdfs:Class rdfs:Property rdfs:subClassOf

RDFS Examples RDF Schema terms (just a few examples): – Class – Property – type – subClassOf – range – domain These terms are the RDF Schema building blocks (constructors) used to create vocabularies:

Problems with RDFS RDFS too weak to describe resources in sufficient detail – No localised range and domain constraints Can’t say that the range of hasChild is person when applied to persons and elephant when applied to elephants – No existence/cardinality constraints Can’t say that all instances of person have a mother that is also a person, or that persons have exactly 2 parents – No transitive, inverse or symmetrical properties Can’t say that isPartOf is a transitive property, that hasPart is the inverse of isPartOf or that touches is symmetrical –…–… Difficult to provide reasoning support – No “native” reasoners for non-standard semantics – May be possible to reason via FO axiomatisation

27 Where to look next RDF: RDF Schema:

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